Conventional traffic prediction methods and systems generally provide an estimation of a general traffic flow through predetermined areas. For example, estimation of traffic flow in proximity of Visual Points of Interest (VPOIs) is a good way to estimate the audience that can potentially view and recognize VPOIs such as: architectural buildings, road traffic signalization, electronic billboards, etc. These predetermined areas from which the audience may be visually exposed to VPOIs can be located near roadways, airports, hotels, shopping centers, etc.
These known traffic estimation methods usually involve vehicle detection solutions and systems that are configured to count a number of vehicles that travel through the predetermined areas. Such vehicle detection solutions may use cameras or human assessors to estimate traffic for the given area.
Vehicle detection solutions which implement cameras may be configured to identify some vehicles that are recognizable via video footage generated by a camera that is installed near and is angled towards the area for recording traffic travelling through it. Such vehicle detection solutions are sensitive and their performance varies with respect to weather, illumination, period of day, degree of traffic as well as quality, location and angle of the camera.
Vehicle detection solutions which implement human assessors are generally directed to the evaluation of a number of vehicles travelling through the area where human assessors are located and are tasked with counting the number of vehicles that they see travelling through the area. Such vehicle detection solutions can be expensive and, for large scale traffic evaluation implementations, may be very difficult to coordinate due to a large number of areas that require traffic evaluation and/or due to large number of vehicles during rush hours, which renders vehicle counting by human assessors nearly impossible. Moreover, potential audience of a VPOI may be difficult to estimate via vehicle detection solutions that rely on human assessors since there might be a significant discrepancy between the area visible to the human assessor for which he is tasked to count the number of vehicles passing through the area and the visual exposure zone of the VPOI from which the VPOI is potentially visible.
Other methods known in the art for estimating traffic in predetermined areas rely on navigational devices associated with vehicles and their positional feedback capabilities. Such traffic estimation methods allow determining a number of vehicles that traveled through a given area based on the positional feedback capabilities of the navigational devices that are within those vehicles. However, such traffic estimation methods may be, in some cases, unreliable or prone to significant estimation errors since they take into account solely the traffic caused by vehicles which are associated with navigational devices.
For the foregoing reasons, there is a need for new methods and systems for generating traffic predictions.